class_docstr: GPT Language Model
code: def forward(
      self, idx: torch.Tensor, targets: Optional[torch.Tensor] = None
  ) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
      x = self.emb_stem(idx)
      x = self.blocks(x)
      x = self.ln_f(x)
      logits = self.head(x)
  
      # if we are given some desired targets also calculate the loss
      loss = None
      if targets is not None:
          loss = F.cross_entropy(
              logits.view(-1, logits.size(-1)),
              targets.view(-1),
              ignore_index=-1,
          )
  
      return logits, loss
  
imports: import math
  from dataclasses import dataclass
  from typing import Optional, Tuple
  import torch
  import torch.nn
  from torch.nn import functional
label_desc: Use image node_id 4 for calling the GPT obj's underlying member method code with example usage: obj.forward(idx, targets) and returns: logits,  loss